> I love tree base algorithm they are so good in many context random forest is delightful in that the algorithm has very few parameters, the default values of

> I love tree base algorithm they are so good in many context random forest is delightful in that the algorithm has very few parameters, the default values of parameters are generally okay, and it generally tends to do something reasonable when you throw it at "real world data" with missing data / categorical variables / useless noise features in the input / etc. Provided a single decision tree does not overfit to then a random forest wont overfit either.